基于多源信息与深度学习特征提取的人口空间抽样方法

人口抽样调查是通过人口样本估算区域人口总体的一种手段.由于人口分布通常具有空间差异性,传统的抽样调查理论难以满足日益增长的空间抽样需求,合理高效的人口空间抽样调查方法对于人口统计、研究人类活动、解决城市问题等有重要意义.本文提出一种基于多源信息与深度学习特征提取的人口空间抽样方法.在不透水面信息的辅助下,利用四叉树分割...

Spatial sampling of population based on multi-source information and deep learning feature extraction

Population sampling survey is a means to estimate the population of a region through population samples. Due to the spatial difference of population distribution, the traditional sampling survey theory is difficult to meet the growing demand of spatial sampling. The research on reasonable and efficient population spatial sampling survey method is of great significance to population statistics, human activities and urban problems. This paper proposes a population spatial sampling method based on multi-source information and deep learning feature extraction. Firstly, we use quadtree segmentation for stratified sampling with the help of impervious surface information, initially select the survey samples that may have population distribution.Secondly, we estimate building density of sample by convolution neural network that is a common model of deep learning to assist in the final sample selection and survey scheme formulation. The results show that this method can effectively screen the sampling areas closely related to population distribution, eliminate a large number of useless samples, improve the efficiency of population survey and save a lot of survey costs.